For some people, parallel computing and the need for a cluster is a way of life. For others, the need sneaks up on them. Most clusters and grids are planned and organized from the first, and that can take time and effort, to say nothing of configuration. Other times there's no budget for new hardware, but there are computer labs or desktop computers unused for much of the day---a cluster waiting to be harnessed, if only you can get the Macs to talk to the Windows boxes, and keep straight all the hostnames in use. For situations like these I helped develop Wolfram Lightweight Grid System, which is designed from the ground up to let you assemble existing hardware into a self-organized network, accessible from Mathematica with almost no configuration.

In the eighties I attended a scientific presentation about a rather cumbersome way to parallelize one of the symbolic computation systems in existence at that time and quickly realized how much more elegantly I could bring parallelism to Mathematica, thanks to its symbolic communication protocol, MathLink. This protocol allowed me to exchange not only data but also programs between concurrently running Mathematica kernels. The result was a package, written entirely in Mathematica, called Parallel Computing Toolkit. At a time when parallel computing meant big expensive machines, FORTRAN, and batch jobs, it was quite satisfying to experiment with different parallel paradigms from an interactive Mathematica notebook, with a couple of machines on a local network doing the computations, and be able to do parallel functional programming and work with symbolic expressions and arbitrary-precision arithmetic in parallel. I got a lot of surprised reactions from people who thought that parallelization is this big complicated thing, requiring supercomputers and large funds, and rather large problems, to be worthwhile. The truth is, most problems people solve are easy to parallelize.